the AI-native open-source embedding database

Angle-optimized Text Embeddings | 🔥 SOTA on STS and MTEB Leaderboard

Vietnamese long form question answering system with documents retrieval.

Implementation of ECIR 2022 Paper: How Can Graph Neural Networks Help Document Retrieval: A Case Study on CORD19 with Concept Map Generation

pgvector + embeddings API

Retrieves the top 10 documents from the Wikipedia corpus for a user inputted free-text query

Document Querying with LLMs - Google PaLM API: Semantic Search With LLM Embeddings

Code and dataset for the paper "Redefining Absent Keyphrases and their Effect on Retrieval Effectiveness"

Client SDK for starpoint.ai

The Intelligent "ASKDOC" project combines the power of Langchain, Azure, OpenAI models, and Python to deliver an intelligent question-answering system, that scans your PDF documents and answer queries based on its contents. It can be queried using Human Natural Language.

A two-stage information retrieval model using baseline TF-IDF model and refined BM25.

Neural text summarization for document retrieval

Automatic structuring of textual computer system logs using document retrieval.

A program to construct and read an inverted index.

An implementation of basic IR techniques from scratch.

This Latent Semantic Indexing [ LSI ] model collects, parses, and stores documents to facilitate fast and accurate information retrieval through queries.

a minimal local embedding database.

Kmeans, Kmeans++, Gaussian Mixtures